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arXiv · 2112.11085

Can We Use Neural Regularization to Solve Depth Super-Resolution?

Milena Gazdieva·Oleg Voynov·Alexey Artemov·Youyi Zheng·Luiz Velho·Evgeny Burnaev
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Abstract

Depth maps captured with commodity sensors often require super-resolution to be used in applications. In this work we study a super-resolution approach based on a variational problem statement with Tikhonov regularization where the regularizer is parametrized with a deep neural network. This approach was previously applied successfully in photoacoustic tomography. We experimentally show that its application to depth map super-resolution is difficult, and provide suggestions about the reasons for that.

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Milena Gazdieva, Oleg Voynov, Alexey Artemov, Youyi Zheng, Luiz Velho, Evgeny Burnaev. 2021-12-21. Can We Use Neural Regularization to Solve Depth Super-Resolution?. https://arxiv.org/abs/2112.11085

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